Business Intelligence as a Clinical Governance Intervention: A Longitudinal Quasi-Experimental Study Protocol in Long-Term Care

Background Long-term care (LTC) systems are subject to increasing demand due to population ageing, multimorbidity, and the sustained complexity of care. This has elevated the need for transparent and effective decision-making. While healthcare organizations routinely generate large volumes of clinical and administrative data, utilization of these data remains fragmented and insufficient to fully support integrated clinical governance. Business Intelligence (BI) has been identified as one potential strategy to address this gap; nonetheless, empirical evidence regarding its effectiveness as a structured organizational intervention, particularly with respect to nursing-sensitive outcomes, is limited. Methods This study protocol outlines a single-center, quasi-experimental longitudinal study using a one-group pretest–posttest design with repeated measures over 12 months following BI implementation. The intervention comprises a structured BI system integrating indicators of structure, process, outcome, and value, combined with data literacy training, monthly indicator-driven clinical governance meetings, and continuous monitoring of key performance indicators. The primary outcome is the Nursing Practice Environment (NPE). Secondary outcomes include missed nursing care, functional gain (ΔFIM), and well-being index (WHO-5). Data will be collected through repeated nurse-level questionnaires and aggregated institutional data. Longitudinal analyses will be conducted using Linear Mixed Models or Generalized Estimating Equations, with adjustment for temporal and contextual factors. Interrupted time series analyses will be applied where appropriate. Mediation models will explore the role of NPE and missed care in linking BI implementation to patient outcomes. Discussion This study conceptualizes BI as a complex organizational intervention that enables data-driven clinical governance. By integrating organizational, process, and outcome indicators within a longitudinal framework, this study aims to generate robust evidence on the mechanisms by which data visibility influences care quality and system performance in LTC. The findings are expected to inform scalable strategies for strengthening healthcare governance and accountability.